research-article

Relationships among problematic smartphone use, mathematics anxiety, learning interest, and achievement: : A multiple mediation model

Authors:

Gang LiAuthors Info & Claims

Volume 129, Issue C

https://doi.org/10.1016/j.chb.2021.107171

Published: 01 April 2022 Publication History

Abstract

This study examined the mediating roles of mathematics anxiety and learning interest between problematic smartphone use and mathematics achievement. After two-stage stratified sampling, 30,601 Chinese fourth-graders participated by completing a paper-based test on mathematics achievement and an online questionnaire that included questions on demographic information as well as the problematic smartphone use, mathematics anxiety, and mathematics learning interest scales. The results showed that (1) smartphone use was more problematic among boys than among girls, and students with a low SES tended to be more problematic smartphone users, (2) problematic smartphone use was negatively correlated with mathematics achievement, (3) mathematics anxiety and learning interest partially mediated the relationship between problematic smartphone use and mathematics achievement, and (4) the relationship between problematic smartphone use and mathematics achievement was serially mediated by mathematics anxiety and then mathematics learning interest. The implications of this study and suggestions for future research are discussed.

Highlights

•

This study examines the relation between PSU by pupils and math achievement.

•

The mediating roles of math anxiety and learning interest are also investigated.

•

PSU was negatively correlated with mathematics achievement.

•

Math anxiety and learning interest played partially mediating roles respectively.

•

Math anxiety and then learning interest also played serially mediating roles.

References

[1]

S. Amez, S. Baert, Smartphone use and academic performance: A literature review, International Journal of Educational Research 103 (2020),.

[2]

M.H. Ashcraft, J.A. Krause, Working memory, math performance, and math anxiety, Psychonomic Bulletin & Review 14 (2007) 243–248,.

[3]

J.M. Boumosleh, D. Jaalouk, Depression, anxiety, and smartphone addiction in university students-A cross sectional study, PLoS One 12 (8) (2017),.

[4]

I. Buil, S. Catalán, E. Martínez, Do clickers enhance learning? A control-value theory approach, Computers & Education 103 (2016) 170–182,.

Digital Library

[5]

P.A. Busch, S. McCarthy, Antecedents and consequences of problematic smartphone use: A systematic literature review of an emerging research area, Computers in Human Behavior 114 (2021),.

Digital Library

[6]

E. Carey, F. Hill, A. Devine, D. Szücs, The chicken or the egg? The direction of the relationship between mathematics anxiety and mathematics performance, Frontiers in Psychology 6 (2016) 1–6,.

[7]

H. Chang, S.L. Beilock, The math anxiety-math performance link and its relation to individual and environmental factors: A review of current behavioral and psychophysiological research, Current Opinion in Behavioral Sciences 10 (2016) 33–38,.

[8]

S.J. Chang, A.V. Witteloostuijn, L. Eden, From the Editors: Common method variance in international business research, Journal of International Business Studies 41 (2010) 178–184,.

[9]

B. Chen, F. Liu, S. Ding, X. Ying, L. Wang, Y. Wen, Gender differences in factors associated with smartphone addiction: A cross-sectional study among medical college students, BMC Psychiatry 17 (1) (2017) 341,.

[10]

Y.F. Chen, S.S. Peng, University students' internet use and its relationships with academic performance, interpersonal relationships, psychosocial adjustment and self-evaluation, CyberPsychology and Behavior 11 (4) (2008) 467–469,.

[11]

China Internet Information Center, The 47^th China statistical report on Internet development, China: China Internet Network Information Center, Beijing, 2021.

[12]

D.A. Cook, A.R. Artino Jr., Motivation to learn: An overview of contemporary theories, Medical Education 50 (10) (2016) 997–1014,.

[13]

S.A. Coombes, T. Higgins, K.M. Gamble, J.H. Cauraugh, C.M. Janelle, Attentional control theory: Anxiety, emotion, and motor planning, Journal of Anxiety Disorders 23 (8) (2009) 1072–1079,.

[14]

J.M. Cortina, What is coefficient alpha? An examination of theory and applications, Journal of Applied Psychology 78 (1) (1993) 98–104,.

[15]

E.L. Deci, R. Koestner, R.M. Ryan, Extrinsic rewards and intrinsic motivation in education: Reconsidered once again, Review of Educational Research 71 (1) (2001) 1–27,.

[16]

E.L. Deci, R.M. Ryan, Intrinsic motivation and self-determination in human behavior, Plenum, New York, NY, 1985,.

[17]

E.L. Deci, R.M. Ryan, Motivation, personality, and development within embedded social contexts: An overview of self-determination theory, in: R.M. Ryan (Ed.), Oxford handbook of human motivation, Oxford University Press, Oxford, UK, 2012, pp. 85–107. http://dx.doi.org/10.1093/oxfordhb/9780195399820.013.0006.

[18]

K. Demirci, M. Akgönül, A. Akpinar, Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students, Journal of Behavioral Addictions 4 (2) (2015) 85–92,.

[19]

N. Derakshan, M.W. Eysenck, Anxiety, processing efficiency, and cognitive performance: New developments from attentional control theory, European Psychologist 14 (2009) 168–176,.

[20]

J.D. Elhai, R.D. Dvorak, J.C. Levine, B.J. Hall, Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology, Journal of Affective Disorders 207 (2017) 251–259,.

[21]

D.M. Erceg-Hurn, V.M. Mirosevich, Modern robust statistical methods: An easy way to maximize the accuracy and power of your research, American Psychologist 63 (7) (2008) 591–601,.

[22]

M.W. Eysenck, N. Derakshan, New perspectives in attentional control theory, Personality and Individual Differences 50 (2011) 955–960,.

[23]

M.W. Eysenck, N. Derakshan, R. Santos, M.G. Calvo, Anxiety and cognitive performance: Attentional control theory, Emotion 7 (2) (2007) 336–353,.

[24]

P.H. Fisher, J. Dobbs-Oates, G.L. Doctoroff, D.H. Arnold, Early math interest and the development of math skills, Journal of Educational Psychology 104 (3) (2012) 673–681,.

[25]

E. Gentina, F. Rowe, Effects of materialism on problematic smartphone dependency among adolescents: The role of gender and gratifications, International Journal of Information Management 54 (2020),.

Digital Library

[26]

D. Gi, Y. Park, M. Kyung, J. Park, Mobile phone dependency and its impacts on adolescents' social and academic behaviors, Computers in Human Behavior 63 (2016) 282–292,.

Digital Library

[27]

K. Gravemeijer, M. Stephan, C. Julie, F.-L. Lin, M. Ohtani, What mathematics education may prepare students for the society of the future?, International Journal of Science and Mathematics Education 15 (2) (2017) 105–123,.

[28]

S. Grigg, H.N. Perera, P. Mcllveen, Z. Svetleff, Relations among math self-efficacy, interest, intentions, and achievement: A social cognitive perspective, Contemporary Educational Psychology 53 (2018) 73–86,.

[29]

N.S. Hawi, M. Samaha, To excel or not to excel: Strong evidence on the adverse effect of smartphone addiction on academic performance, Computers & Education 98 (2016) 81–89,.

Digital Library

[30]

A.F. Hayes, J.J. Coutts, Use omega rather than Cronbach's alpha for estimating reliability. But, Communication Methods and Measures 14 (1) (2020) 1–24,.

[31]

A. Heinze, K. Reiss, R. Franziska, Mathematics achievement and interest in mathematics from a differential perspective, ZDM 37 (3) (2005) 212–220,.

[32]

R. Hembree, The nature, effects, and relief of mathematics anxiety, Journal for Research in Mathematics Education 21 (1) (1990) 33–46,.

[33]

S. Hidi, K.A. Renninger, The four-phase model of interest development, Educational Psychologist 41 (2006) 111–127,.

[34]

J. Horvath, C. Mundinger, M.M. Schmitgen, N.D. Wolf, F. Sambataro, D. Hirjak, K.M. Kubera, J. Koenjg, R.C. Wolf, Structural and functional correlates of smartphone addiction, Addictive Behaviors 105 (2020),.

[35]

L.T. Hu, P.M. Bentler, Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling 6 (1) (1999) 1–55,.

[36]

International Telecommunication Union (ITU) (2020) : https://www.itu.int/en/ITU-D/Statistics/Pages/publications/default.aspx.

[37]

M.M. Jameson, Contextual factors related to math anxiety in second-grade children, The Journal of Experimental Education 82 (2014) 518–536,.

[38]

R.B. Johnson, L.B. Christensen, Educational research: Quantitative, qualitative, and mixed approaches, United States: SAGE, Los Angeles, 2019.

[39]

R. Junco, S.R. Cotten, No A 4 U: The relationship between multitasking and academic performance, Computers & Education 59 (2012) 505–514,.

Digital Library

[40]

M.J. Justicia-Galiano, M.E. Martin-Puga, R. Linares, S. Pelegrina, Math anxiety and math performance in children: The mediating roles of working memory and math self-concept, British Journal of Educational Psychology 87 (4) (2017) 573–589,.

[41]

D. Kardefelt-Winther, A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use, Computers in Human Behavior 31 (2014) 351–354,.

Digital Library

[42]

A.C. Karpinski, P.A. Kirschner, I. Ozer, J.A. Mellott, P. Ochwo, An exploration of social networking site use, multitasking, and academic performance among United States and European university students, Computers in Human Behavior 29 (2013) 1182–1192,.

Digital Library

[43]

A.W. Kates, H. Wu, C.L.S. Coryn, The effects of mobile phone use on academic performance: A meta analysis, Computers & Education 127 (2018) 107–112,.

[44]

L. Kibona, G. Mgaya, Smartphones' effects on academic performance of higher learning students, Journal of Multidisciplinary Engineering Science and Technology 2 (4) (2015) 777–784.

[45]

D. Kim, Y. Lee, J. Lee, J.K. Nam, Y. Chung, Development of Korean smartphone addiction proneness scale for Youth, PLoS One 9 (5) (2014),.

[46]

R.B. Kline, Principles and practice of structural equation modeling, The Guilford Press, New York, 2010.

[47]

F. Kong, J. Qin, B. Huang, H. Zhang, L. Lei, The effect of social anxiety on mobile phone dependence among Chinese adolescents: A moderated mediation model, Children and Youth Services Review 108 (2020),.

[48]

A. Krapp, Structural and dynamic aspects of interest development: Theoretical considerations from an ontogenetic perspective, Learning and Instruction 12 (2002) 383–409,.

[49]

X. Lai, S. Huang, C. Zhang, B. Tang, M. Zhang, C. Zhu, Y. Wang, The association between smartphone addiction, interpersonal relationships, subjective well-being and school identity among primary and middle school students, Chinese Journal of School Health 41 (4) (2020) 613–616,.

[50]

J. Lee, B. Cho, Y. Kim, J. Noh, Smartphone addiction in university students and its implication for learning, in: G. Chen, V. Kumar, R.H. Kinshuk, S.C. Kong (Eds.), Emerging issues in smart learning, Springer, Berlin, Heidelberg, 2015, pp. 297–305,.

[51]

A. Lepp, J.E. Barkley, A.C. Karpinski, The relationship between cell phone use, academic performance, anxiety, and satisfaction with life in college students, Computers in Human Behavior 31 (2014) 343–350,.

Digital Library

[52]

L. Li, H. Gao, Y. Xu, The mediating and buffering effect of academic self-efficacy on the relationship between smartphone addiction and academic procrastination, Computers & Education 159 (2020),.

[53]

L. Li, S. Mei, Z. Niu, Y. Song, Loneliness and sleep quality in university students: Mediator of smartphone addiction and moderator of gender, Chinese Journal of Clinical Psychology 24 (2) (2016) 345–348,.

[54]

Y. Lin, Q. Liu, Perceived subjective social status and smartphone addiction tendency among Chinese adolescents: A sequential mediation model, Children and Youth Services Review 116 (2020),.

[55]

Q. Liu, X. Du, S. Zhao, J. Liu, J. Cai, The role of memorization in students' self-reported mathematics learning: A large-scale study of Chinese eighth-grade students, Asia Pacific Education Review 20 (2019) 361–374,.

[56]

X. Ma, Assessing the relationship between attitude toward mathematics and achievement in mathematics: A meta-analysis, Journal for Research in Mathematics Education 30 (5) (1999) 520–540,.

[57]

M. Malanchini, K. Rimfeld, N.G. Shakeshaft, M. Rodic, K. Schofield, Y. Kovas, The genetic and environmental aetiology of spatial, mathematics and general anxiety, Scientific Reports 7 (2017),.

[58]

E.A. Maloney, S.L. Beilock, Math anxiety: Who has it, why it develops, and how to guard against it, Trends in Cognitive Sciences 16 (8) (2012) 404–406,.

[59]

D.M. McInerney, R.W.Y. Cheng, M.M.C. Mok, A.K.H. Lam, Academic self-concept and learning strategies direction of effect on student academic achievement, Journal of Advanced Academics 23 (3) (2012) 249–269,.

[60]

J.K. Nayak, Relationship among smartphone usage, addiction, academic performance and the moderating role of gender: A study of higher education students in India, Computers & Education 123 (2018) 164–173,.

Digital Library

[61]

Organisation for Economic Co-Operation and Development [OECD], PISA 2015 technical report, 2017, Retrieved from http://www.oecd.org/pisa/sitedocument/PISA-2015-technical-report-final.pdf.

[62]

R. Pekrun, A social cognitive, control-value theory of achievement emotions, in: J. Heckhausen (Ed.), Motivational psychology of human development, Elsevier, Oxford, England, 2000, pp. 143–163.

[63]

R. Pekrun, The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice, Educational Psychology Review 18 (4) (2006) 315–341,.

[64]

R. Pekrun, A. Elliot, M. Maier, Achievement goals and discrete achievement emotions: A theoretical model and prospective test, Journal of Educational Psychology 98 (2006) 583–597,.

[65]

R. Pekrun, T. Goetz, A. Frenzel, P. Barchfeld, R. Perry, Measuring emotions in students' learning and performance: The achievement emotions questionnaire (AEQ), Contemporary Educational Psychology 36 (1) (2011) 36–48,.

[66]

R. Pekrun, T. Goetz, W. Titz, R. Perry, Academic emotions in students' self-regulated learning and achievement: A program of qualitative and quantitative research, Educational Psychologist 37 (2) (2002) 91–106,.

[67]

R. Pekrun, R.P. Perry, Control-value theory of achievement emotions, in: R. Pekrun, L. Linnenbrink-Garcia (Eds.), International handbook of emotions in education, Routledge, New York, 2014, pp. 120–141,.

[68]

P.M. Podsakoff, S.B. MacKenzie, J.Y. Lee, N.P. Podsakoff, Common method biases in behavioral research: A critical review of the literature and recommended remedies, Journal of Applied Psychology 88 (5) (2013) 879–903,.

[69]

D. Raufelder, N. Regner, M.A. Wood, Test anxiety and learned helplessness is moderated by student perceptions of teacher motivational support, Educational Psychology 38 (1) (2018) 54–74,.

[70]

K. Renninger, H.S. Ann, A. Krapp, The role of interest in learning and development, Lawrence Erlbaum Associates, Hillsdale, NJ, 1992.

[71]

R. Rosenman, V. Tennekoon, L. Hill, Measuring bias in self-reported data, International Journal of Behavioural and Healthcare Research 2 (2) (2011) 320–332,.

[72]

D. Rozgonjuk, J.C. Levine, B.J. Hall, J.D. Elhai, The association between problematic smartphone use, depression and anxiety symptom severity, and objectively measured smartphone use over one week, Computers in Human Behavior 87 (2018) 10–17,.

Digital Library

[73]

M. Samaha, N.S. Hawi, Relationships among smartphone addiction, stress, academic performance and satisfaction with life, Computers in Human Behavior 57 (2016) 321–325,.

Digital Library

[74]

P. Scherer, H. Steinbring, Inter-relating theory and practice in mathematics teacher education, Journal of Mathematics Teacher Education 9 (2006) 103–108,.

[75]

U. Schiefele, The role of interest in motivation and learning, in: J.M. Collis, S. Messick (Eds.), Intelligence and personality: Bridging the gap between theory and measurement, Erlbaum, Mahwah, NJ, 2001, pp. 167–199.

[76]

D.G. Seo, Y. Park, M. Mize, J. Park, Mobile phone dependency and its impacts on adolescents' social and academic behaviors, Computers in Human Behavior 63 (2016) 282–292,.

Digital Library

[77]

B.F. Sherman, D.P. Wither, Mathematics anxiety and mathematics achievement, Mathematics Education Research Journal 15 (2003) 138–150,.

[78]

K. Singh, M. Granville, S. Dika, Mathematics and science achievement: Effects of motivation, interest, and academic engagement, The Journal of Educational Research 95 (6) (2002) 323–332,.

[79]

S.Y. Sohn, P. Rees, B. Wildridge, N.J. Kalk, B. Carter, Prevalence of problematic smartphone usage and associated mental health outcomes amongst children and young people: A systematic review, meta-analysis and GRADE of the evidence, BMC Psychiatry 19 (356) (2019),.

[80]

R. Sorvo, T. Koponen, H. Viholainen, T. Aro, E. Räikkönen, P. Peura, M. Aro, Math anxiety and its relationship with basic arithmetic skills among primary school children, British Journal of Educational Psychology 87 (3) (2017) 309–327,.

[81]

Statista (2021) : https://www.statista.com/topics/2711/us-smartphone-market/.

[82]

J. Sun, Z. Li, N. Buys, E.A. Storch, Correlates of comorbid depression, anxiety and helplessness with obsessive–compulsive disorder in Chinese adolescents, Journal of Affective Disorders 174 (15) (2015) 31–37,.

[83]

S. Tao, X. Wu, S. Zhang, S. Tong, J. Hao, F. Tao, Association of alcohol use with problematic mobile phone use and depressive symptoms among college students in Anhui, China, Journal of Public Health 25 (2017) 103–112,.

[84]

S. Tehseen, T. Ramayah, S. Sajilan, Testing and controlling for common method variance: A review of available methods, Journal of Management Sciences 4 (2) (2017) 146–175,.

[85]

S. Thomée, A. Härenstam, M. Hagberg, Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults: A prospective cohort study, BMC Public Health 11 (66) (2011),.

[86]

S. Ufer, S. Rach, T. Kosiol, Interest in mathematics=interest in mathematics? What general measures of interest reflect when the object of interest changes, ZDM 49 (3) (2017) 397–409,.

[87]

A.J.A.M. Van Deursen, C.L. Bolle, S.M. Hegner, P.A.M. Kommers, Modeling habitual and addictive smartphone behavior: The role of smartphone usage types, emotional intelligence, social stress, self-regulation, age, and gender, Computers in Human Behavior 45 (2015) 411–420,.

Digital Library

[88]

M Vezzoli, A Colombo, A Marano, G Zoccatelli, C Zogmaister, Test for Mobile phone dependence: Psychometric properties and confirmatory factor analysis, Current Psychology (2021),.

[89]

J.L. Wang, H.Z. Wang, J. Gaskin, L.H. Wang, The role of stress and motivation in problematic smartphone use among college students, Computers in Human Behavior 53 (2015) 181–188,.

Digital Library

[90]

M.W. Watkins, The reliability of multidimensional neuropsychological measures: From alpha to omega, The Clinical Neuropsychologist 31 (6–7) (2017) 1113–1126,.

[91]

B. Weiner, Intrapersonal and interpersonal theories of motivation from an attributional perspective, Educational Psychology Review 12 (2000) 1–14,.

[92]

Z.L. Wen, K.T. Hau, H.W. Marsh, Structural equation model testing: Cutoff criteria for goodness of fit indices and Chi-square test [Chinese], Acta Psychology Sinica 36 (2004) 186–194.

[93]

M. Wilson, J. Zietz, Systematic bias in student self-reported data, Journal for Economic Educators 4 (4) (2004) 13–19.

[94]

H. Winskel, T.H. Kim, L. Kardash, I. Belic, Smartphone use and study behavior: A Korean and Australian comparison, Heliyon 5 (7) (2019),.

[95]

Y.S. Yang, J.Y. Yen, C.H. Ko, C.P. Cheng, C.F. Yen, The association between problematic cellular phone use and risky behaviors and low self-esteem among Taiwanese adolescents, BMC Public Health 10 (217) (2010),.

[96]

X.J. Yang, Z.K. Zhou, Q.Q. Liu, C.Y. Fan, Mobile phone addiction and adolescents' anxiety and depression: The moderating role of mindfulness, Journal of Child and Family Studies 28 (3) (2019) 822–830,.

[97]

C.F. Yen, C.H. Ko, J.Y. Yen, Y.P. Chang, C.P. Cheng, Multi-dimensional discriminative factors for Internet addiction among adolescents regarding gender and age, Psychiatry and Clinical Neurosciences 63 (3) (2009) 357–364,.

[98]

L. Ye, M. Recker, A. Walker, H. Leary, M. Yuan, Expanding approaches for understanding impact: Integrating technology, curriculum, and open educational resources in science education, Educational Technology Research & Development 63 (2015) 355–380,.

[99]

D. Zhang, C. Wang, The relationship between mathematics interest and mathematics achievement: Mediating roles of self-efficacy and mathematics anxiety, International Journal of Educational Research 104 (2020),.

[100]

D. Zhou, X.F. Du, K.T. Hau, H.F. Luo, P.T. Feng, J. Liu, Teacher-student relationship and mathematical problem-solving ability: Mediating roles of self-efficacy and mathematical anxiety, Educational Psychology 40 (4) (2020) 473–489,.

[101]

D. Zhou, J.Q. Liu, J. Liu, The effect of problematic Internet use on mathematics achievement: The mediating role of self-efficacy and the moderating role of teacher-student relationships, Children and Youth Services Review 118 (2020),.

[102]

D. Zhou, J. Liu, J. Liu, On the different effects of teacher–student rapport on urban and rural students' math learning in China: An empirical study, Psychology in the Schools 58 (2) (2021) 268–285,.

Cited By

Gutierrez-Aguilar ODuche Pérez ALeon-Lucano JCordova-Buiza FChicaña-Huanca S(2023)Cell Phone Addiction, Anxiety and Distraction and Their Relationship to Learning AchievementProceedings of the 18th Latin American Conference on Learning Technologies (LACLO 2023)10.1007/978-981-99-7353-8_2(14-25)Online publication date: 18-Oct-2023
https://dl.acm.org/doi/10.1007/978-981-99-7353-8_2
Hong JHsu SKao CChen W(2023)Learning English via Virtual Charades with Google Assistant: The Correlates Between Smartphone Self-efficacy, Interactive Fun, Flow Experience and Learning OutcomesSmart Learning for A Sustainable Society10.1007/978-981-99-5961-7_24(197-202)Online publication date: 31-Aug-2023
https://dl.acm.org/doi/10.1007/978-981-99-5961-7_24

Index Terms

Relationships among problematic smartphone use, mathematics anxiety, learning interest, and achievement: A multiple mediation model

Index terms have been assigned to the content through auto-classification.

Recommendations

The effects of computer-assisted instruction on the achievement, attitudes and retention of fourth grade mathematics students in North Cyprus

The purpose of this study was to examine the effects of the educational software Frizbi Mathematics 4 on 4th grade student's mathematics achievement, retention, attitudes toward mathematics and attitude toward computer assisted learning. Two groups (...
Mathematics Self- Efficacy, Mathematics Anxiety, Community of Inquiry, and Mathematics Engagement of Performance in Mathematics among College Students using an Online Learning Modality
ICEMT '23: Proceedings of the 7th International Conference on Education and Multimedia Technology

The study investigated whether self-efficacy and anxiety in mathematics, engagement and community of inquiry predicts mathematics performance among Filipino college students. Since 2020, the COVID pandemic has hit the world and it has left schools to ...
Social anxiety and social skills via problematic smartphone use for predicting somatic symptoms and academic performance at primary school
Abstract
Mobile phones have become an indispensable tool in different areas of life, however this often results in some negative effects, especially among their youngest users. The aim of the present study is to analyze the relationship between ...
Highlights
- Social skills was positively related to grade point average (GPA).
- Problematic ...

Comments

Information & Contributors

Information

Published In

cover image Computers in Human Behavior

Computers in Human Behavior Volume 129, Issue C

Apr 2022

349 pages

ISSN:0747-5632

Issue’s Table of Contents

Elsevier Ltd.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 April 2022

Author Tags

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 01 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Gutierrez-Aguilar ODuche Pérez ALeon-Lucano JCordova-Buiza FChicaña-Huanca S(2023)Cell Phone Addiction, Anxiety and Distraction and Their Relationship to Learning AchievementProceedings of the 18th Latin American Conference on Learning Technologies (LACLO 2023)10.1007/978-981-99-7353-8_2(14-25)Online publication date: 18-Oct-2023
https://dl.acm.org/doi/10.1007/978-981-99-7353-8_2
Hong JHsu SKao CChen W(2023)Learning English via Virtual Charades with Google Assistant: The Correlates Between Smartphone Self-efficacy, Interactive Fun, Flow Experience and Learning OutcomesSmart Learning for A Sustainable Society10.1007/978-981-99-5961-7_24(197-202)Online publication date: 31-Aug-2023
https://dl.acm.org/doi/10.1007/978-981-99-5961-7_24

View Options

View options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Issue’s Table of Contents